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Found 14 papers, 5 papers with code
Automatic Fake News Detection: Are current models “fact-checking” or“gut-checking”?
Automatic fake news detection models are ostensibly based on logic, where the truth of a claim made in a headline can be determined by supporting or refuting evidence found in a resulting web query.
A Simple Unsupervised Approach for Coreference Resolution using Rule-based Weak Supervision
Labeled data for the task of Coreference Resolution is a scarce resource, requiring significant human effort.
Greed is All You Need: An Evaluation of Tokenizer Inference Methods
While subword tokenizers such as BPE and WordPiece are typically used to build vocabularies for NLP models, the method of decoding text into a sequence of tokens from these vocabularies is often left unspecified, or ill-suited to the method in which they were constructed.
Tokenization Is More Than Compression
Tokenization is a foundational step in Natural Language Processing (NLP) tasks, bridging raw text and language models.
DocFinQA: A Long-Context Financial Reasoning Dataset
For large language models (LLMs) to be effective in the financial domain -- where each decision can have a significant impact -- it is necessary to investigate realistic tasks and data.
BizBench: A Quantitative Reasoning Benchmark for Business and Finance
We demonstrate that the current bottleneck in performance is due to LLMs' limited business and financial understanding, highlighting the value of a challenging benchmark for quantitative reasoning within this domain.
A Graphical Approach to Document Layout Analysis
Document layout analysis (DLA) is the task of detecting the distinct, semantic content within a document and correctly classifying these items into an appropriate category (e. g., text, title, figure).
Ranked #13 on
Document Layout Analysis
on PubLayNet val
What happens before and after: Multi-Event Commonsense in Event Coreference Resolution
Event coreference models cluster event mentions pertaining to the same real-world event.
LineCap: Line Charts for Data Visualization Captioning Models
Data visualization captions help readers understand the purpose of a visualization and are crucial for individuals with visual impairments.
What GPT Knows About Who is Who
Coreference resolution -- which is a crucial task for understanding discourse and language at large -- has yet to witness widespread benefits from large language models (LLMs).
Evaluating the Fairness Impact of Differentially Private Synthetic Data
Differentially private (DP) synthetic data is a promising approach to maximizing the utility of data containing sensitive information.
Automatic Fake News Detection: Are current models "fact-checking" or "gut-checking"?
Automatic fake news detection models are ostensibly based on logic, where the truth of a claim made in a headline can be determined by supporting or refuting evidence found in a resulting web query.
Building astroBERT, a language model for Astronomy & Astrophysics
The existing search tools for exploring the NASA Astrophysics Data System (ADS) can be quite rich and empowering (e. g., similar and trending operators), but researchers are not yet allowed to fully leverage semantic search.
